{"title":"基于集成卡尔曼滤波的二自由度直升机显式非线性模型预测控制设计","authors":"Lakshmi Dutta, Dushmanta Kumar Das","doi":"10.1109/ComPE49325.2020.9200043","DOIUrl":null,"url":null,"abstract":"This research work develops an explicit nonlinear model predictive control strategy for an aerodynamical model i.e. twin rotor MIMO system (TRMS). Here the control strategy is developed by calculating the tracking error as well as the control signal in the prediction horizon using Taylor series expansion. The explicit solution for the control signal is obtained from an optimal performance index which can be developed without online optimization. The complete state information of the system to the proposed controller is given from an ensemble Kalman filter (EnKF) based state observer. The simulation and real-time results are documented in graphical form to confirm the efficiency of the proposed controller.","PeriodicalId":6804,"journal":{"name":"2020 International Conference on Computational Performance Evaluation (ComPE)","volume":"59 1","pages":"033-038"},"PeriodicalIF":0.0000,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Ensemble Kalman Filter based Explicit Nonlinear Model Predictive Control Design for Two Degree Freedom of Helicopter Model\",\"authors\":\"Lakshmi Dutta, Dushmanta Kumar Das\",\"doi\":\"10.1109/ComPE49325.2020.9200043\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This research work develops an explicit nonlinear model predictive control strategy for an aerodynamical model i.e. twin rotor MIMO system (TRMS). Here the control strategy is developed by calculating the tracking error as well as the control signal in the prediction horizon using Taylor series expansion. The explicit solution for the control signal is obtained from an optimal performance index which can be developed without online optimization. The complete state information of the system to the proposed controller is given from an ensemble Kalman filter (EnKF) based state observer. The simulation and real-time results are documented in graphical form to confirm the efficiency of the proposed controller.\",\"PeriodicalId\":6804,\"journal\":{\"name\":\"2020 International Conference on Computational Performance Evaluation (ComPE)\",\"volume\":\"59 1\",\"pages\":\"033-038\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 International Conference on Computational Performance Evaluation (ComPE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ComPE49325.2020.9200043\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Conference on Computational Performance Evaluation (ComPE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ComPE49325.2020.9200043","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Ensemble Kalman Filter based Explicit Nonlinear Model Predictive Control Design for Two Degree Freedom of Helicopter Model
This research work develops an explicit nonlinear model predictive control strategy for an aerodynamical model i.e. twin rotor MIMO system (TRMS). Here the control strategy is developed by calculating the tracking error as well as the control signal in the prediction horizon using Taylor series expansion. The explicit solution for the control signal is obtained from an optimal performance index which can be developed without online optimization. The complete state information of the system to the proposed controller is given from an ensemble Kalman filter (EnKF) based state observer. The simulation and real-time results are documented in graphical form to confirm the efficiency of the proposed controller.